#include "dropout_layer.h"
#include "utils.h"
#include "cuda.h"
#include <stdlib.h>
#include <stdio.h>

dropout_layer make_dropout_layer(int batch, int inputs, float probability)
{
    dropout_layer l = {0};
    l.type = DROPOUT;
    l.probability = probability;
    l.inputs = inputs;
    l.outputs = inputs;
    l.batch = batch;
    l.rand = calloc(inputs * batch, sizeof(float));
    l.scale = 1. / (1. - probability);
    l.forward = forward_dropout_layer;
    l.backward = backward_dropout_layer;
#ifdef GPU
    l.forward_gpu = forward_dropout_layer_gpu;
    l.backward_gpu = backward_dropout_layer_gpu;
    l.rand_gpu = cuda_make_array(l.rand, inputs * batch);
#endif
    fprintf(stderr, "dropout       p = %.2f               %4d  ->  %4d\n", probability, inputs, inputs);
    return l;
}

void resize_dropout_layer(dropout_layer *l, int inputs)
{
    l->rand = realloc(l->rand, l->inputs * l->batch * sizeof(float));
#ifdef GPU
    cuda_free(l->rand_gpu);

    l->rand_gpu = cuda_make_array(l->rand, inputs * l->batch);
#endif
}

void forward_dropout_layer(dropout_layer l, network_state state)
{
    int i;

    if (!state.train)
    {
        return;
    }

    for (i = 0; i < l.batch * l.inputs; ++i)
    {
        float r = rand_uniform(0, 1);
        l.rand[i] = r;

        if (r < l.probability)
        {
            state.input[i] = 0;
        }
        else
        {
            state.input[i] *= l.scale;
        }
    }
}

void backward_dropout_layer(dropout_layer l, network_state state)
{
    int i;

    if (!state.delta)
    {
        return;
    }

    for (i = 0; i < l.batch * l.inputs; ++i)
    {
        float r = l.rand[i];

        if (r < l.probability)
        {
            state.delta[i] = 0;
        }
        else
        {
            state.delta[i] *= l.scale;
        }
    }
}

